----------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/nravanilla/Desktop/Senate Pork Replication Files/senate_pork.log
  log type:  text
 opened on:  29 Apr 2022, 14:30:14

. 
. set more off

. 
. *Generate election year dummies
. tab year, gen(year)

       year |      Freq.     Percent        Cum.
------------+-----------------------------------
       2001 |         46        8.33        8.33
       2002 |         46        8.33       16.67
       2003 |         46        8.33       25.00
       2004 |         46        8.33       33.33
       2005 |         46        8.33       41.67
       2006 |         46        8.33       50.00
       2007 |         46        8.33       58.33
       2008 |         46        8.33       66.67
       2009 |         46        8.33       75.00
       2010 |         46        8.33       83.33
       2011 |         46        8.33       91.67
       2012 |         46        8.33      100.00
------------+-----------------------------------
      Total |        552      100.00

. gen elec_yr1=0

. replace elec_yr1=1 if year==2002 | year==2003 | year==2004
(138 real changes made)

. gen elec_yr2=0

. replace elec_yr2=1 if year==2005 | year==2006 | year==2007
(138 real changes made)

. gen elec_yr3=0

. replace elec_yr3=1 if year==2008 | year==2009 | year==2010
(138 real changes made)

. gen elec_yr4=0

. replace elec_yr4=1 if year==2011 | year==2012
(92 real changes made)

. 
. 
. **************************************************************************************
. *Figure 1: CDF Funds (in million pesos) by Senatorial Reelectionist Status, 2001--2012
. **************************************************************************************
. 
. preserve

. 
. replace cdf_targeted=cdf_targeted/1000000
variable cdf_targeted was long now double
(148 real changes made)

. 
. collapse (mean) mean=cdf_targeted (sd) sd=cdf_targeted (count) n=cdf_targeted, by(reelectionist year)

. generate hipdaf=mean + invttail(n-1,0.025)*(sd/sqrt(n))
(18 missing values generated)

. generate lopdaf=mean - invttail(n-1,0.025)*(sd/sqrt(n))
(18 missing values generated)

. 
. generate year_match=1 if year==2001 & reelectionist==1
(35 missing values generated)

. replace year_match=2 if year==2001 & reelectionist==0
(1 real change made)

. replace year_match=4 if year==2002 & reelectionist==1
(1 real change made)

. replace year_match=5 if year==2002 & reelectionist==0
(1 real change made)

. replace year_match=7 if year==2003 & reelectionist==1
(1 real change made)

. replace year_match=8 if year==2003 & reelectionist==0
(1 real change made)

. replace year_match=10 if year==2004 & reelectionist==1
(1 real change made)

. replace year_match=11 if year==2004 & reelectionist==0
(1 real change made)

. replace year_match=13 if year==2005 & reelectionist==1
(1 real change made)

. replace year_match=14 if year==2005 & reelectionist==0
(1 real change made)

. replace year_match=16 if year==2006 & reelectionist==1
(1 real change made)

. replace year_match=17 if year==2006 & reelectionist==0
(1 real change made)

. replace year_match=19 if year==2007 & reelectionist==1
(1 real change made)

. replace year_match=20 if year==2007 & reelectionist==0
(1 real change made)

. replace year_match=22 if year==2008 & reelectionist==1
(1 real change made)

. replace year_match=23 if year==2008 & reelectionist==0
(1 real change made)

. replace year_match=25 if year==2009 & reelectionist==1
(1 real change made)

. replace year_match=26 if year==2009 & reelectionist==0
(1 real change made)

. replace year_match=28 if year==2010 & reelectionist==1
(1 real change made)

. replace year_match=29 if year==2010 & reelectionist==0
(1 real change made)

. replace year_match=31 if year==2011 & reelectionist==1
(1 real change made)

. replace year_match=32 if year==2011 & reelectionist==0
(1 real change made)

. replace year_match=34 if year==2012 & reelectionist==1
(1 real change made)

. replace year_match=35 if year==2012 & reelectionist==0
(1 real change made)

. 
. graph twoway (bar mean year_match if reelectionist==1) (bar mean year_match if reelectionist==0)(rcap hipdaf l
> opdaf year_match if reelectionist==1)

. 
. graph export fig1a.pdf,replace
(file /Users/nravanilla/Desktop/Senate Pork Replication Files/fig1a.pdf written in PDF format)

. 
. restore

. 
. 
. preserve

. 
. gen cdf_nt = cdf - cdf_targeted
(404 missing values generated)

. replace cdf_nt=. if cdf==. | cdf_targeted==.
(0 real changes made)

. 
. replace cdf_nt=cdf_nt/1000000
(115 real changes made)

. 
. collapse (mean) mean=cdf_nt (sd) sd=cdf_nt (count) n=cdf_nt, by(reelectionist year)

. generate hipdaf=mean + invttail(n-1,0.025)*(sd/sqrt(n))
(18 missing values generated)

. generate lopdaf=mean - invttail(n-1,0.025)*(sd/sqrt(n))
(18 missing values generated)

. 
. generate year_match=1 if year==2001 & reelectionist==1
(35 missing values generated)

. replace year_match=2 if year==2001 & reelectionist==0
(1 real change made)

. replace year_match=4 if year==2002 & reelectionist==1
(1 real change made)

. replace year_match=5 if year==2002 & reelectionist==0
(1 real change made)

. replace year_match=7 if year==2003 & reelectionist==1
(1 real change made)

. replace year_match=8 if year==2003 & reelectionist==0
(1 real change made)

. replace year_match=10 if year==2004 & reelectionist==1
(1 real change made)

. replace year_match=11 if year==2004 & reelectionist==0
(1 real change made)

. replace year_match=13 if year==2005 & reelectionist==1
(1 real change made)

. replace year_match=14 if year==2005 & reelectionist==0
(1 real change made)

. replace year_match=16 if year==2006 & reelectionist==1
(1 real change made)

. replace year_match=17 if year==2006 & reelectionist==0
(1 real change made)

. replace year_match=19 if year==2007 & reelectionist==1
(1 real change made)

. replace year_match=20 if year==2007 & reelectionist==0
(1 real change made)

. replace year_match=22 if year==2008 & reelectionist==1
(1 real change made)

. replace year_match=23 if year==2008 & reelectionist==0
(1 real change made)

. replace year_match=25 if year==2009 & reelectionist==1
(1 real change made)

. replace year_match=26 if year==2009 & reelectionist==0
(1 real change made)

. replace year_match=28 if year==2010 & reelectionist==1
(1 real change made)

. replace year_match=29 if year==2010 & reelectionist==0
(1 real change made)

. replace year_match=31 if year==2011 & reelectionist==1
(1 real change made)

. replace year_match=32 if year==2011 & reelectionist==0
(1 real change made)

. replace year_match=34 if year==2012 & reelectionist==1
(1 real change made)

. replace year_match=35 if year==2012 & reelectionist==0
(1 real change made)

. 
. graph twoway (bar mean year_match if reelectionist==1) (bar mean year_match if reelectionist==0)(rcap hipdaf l
> opdaf year_match if reelectionist==1)

. restore

. 
. graph export fig1b.pdf,replace
(file /Users/nravanilla/Desktop/Senate Pork Replication Files/fig1b.pdf written in PDF format)

. 
. 
. **********************************************
. *Table 1: Summary Statistics and Balance Tests
. **********************************************
. 
. preserve

. putexcel set tab1.xls, sheet(sheet1) replace
Note: file will be replaced when the first putexcel command is issued

. 
. putexcel A1 = "Variable"
file tab1.xls saved

. putexcel B1 = "Full Sample"
file tab1.xls saved

. putexcel C1 = "Non-Reelectionist (NR)"
file tab1.xls saved

. putexcel D1 = "Reelectionist (R)"
file tab1.xls saved

. putexcel E1 = "P-values (NR=R)"
file tab1.xls saved

. 
. putexcel A2 = "Number of observations"
file tab1.xls saved

. putexcel B2 = "160"
file tab1.xls saved

. putexcel C2 = "101"
file tab1.xls saved

. putexcel D2 = "59"
file tab1.xls saved

. 
. putexcel A4 = "Panel A: Observables"
file tab1.xls saved

. 
. putexcel A6 = "Female (indicator)"
file tab1.xls saved

. putexcel A8 = "Years of experience"
file tab1.xls saved

. putexcel A10 = "Officer (indicator)"
file tab1.xls saved

. putexcel A12 = "Celebrity (indicator)"
file tab1.xls saved

. putexcel A14 = "Regional following (indicator)"
file tab1.xls saved

. putexcel A16 = "Term-ender (indicator)"
file tab1.xls saved

. 
. putexcel A18 = "Panel B: Outcome Variables"
file tab1.xls saved

. 
. putexcel A20 = "Total CDF"
file tab1.xls saved

. putexcel A21 = "Utilization"
file tab1.xls saved

. putexcel A23 = "Ratio of Targeted to Total"
file tab1.xls saved

. putexcel A25 = "Targeted to Home Province"
file tab1.xls saved

. putexcel A27 = "Herfindahl Index of Targeted"
file tab1.xls saved

. 
. putexcel B6 = "0.15"
file tab1.xls saved

. putexcel B7 = "(0.36)"
file tab1.xls saved

. putexcel B8 = "8.34"
file tab1.xls saved

. putexcel B9 = "(5.41)"
file tab1.xls saved

. putexcel B10 = "0.17"
file tab1.xls saved

. putexcel B11 = "(0.38)"
file tab1.xls saved

. putexcel B12 = "0.24"
file tab1.xls saved

. putexcel B13 = "(0.43)"
file tab1.xls saved

. putexcel B14 = "0.30"
file tab1.xls saved

. putexcel B15 = "(0.46)"
file tab1.xls saved

. putexcel B16 = "0.11"
file tab1.xls saved

. putexcel B17 = "(0.31)"
file tab1.xls saved

. putexcel B21 = "0.54"
file tab1.xls saved

. putexcel B22 = "(0.36)"
file tab1.xls saved

. putexcel B23 = "0.65"
file tab1.xls saved

. putexcel B24 = "(0.35)"
file tab1.xls saved

. putexcel B25 = "0.19"
file tab1.xls saved

. putexcel B26 = "(0.28)"
file tab1.xls saved

. putexcel B27 = "0.27"
file tab1.xls saved

. putexcel B28 = "(0.27)"
file tab1.xls saved

. 
. putexcel C6 = "0.14"
file tab1.xls saved

. putexcel C7 = "(0.35)"
file tab1.xls saved

. putexcel C8 = "8.78"
file tab1.xls saved

. putexcel C9 = "(5.99)"
file tab1.xls saved

. putexcel C10 = "0.15"
file tab1.xls saved

. putexcel C11 = "(0.36)"
file tab1.xls saved

. putexcel C12 = "0.26"
file tab1.xls saved

. putexcel C13 = "(0.44)"
file tab1.xls saved

. putexcel C14 = "0.30"
file tab1.xls saved

. putexcel C15 = "(0.46)"
file tab1.xls saved

. putexcel C16 = "0.17"
file tab1.xls saved

. putexcel C17 = "(0.38)"
file tab1.xls saved

. putexcel C21 = "0.48"
file tab1.xls saved

. putexcel C22 = "(0.34)"
file tab1.xls saved

. putexcel C23 = "0.68"
file tab1.xls saved

. putexcel C24 = "(0.36)"
file tab1.xls saved

. putexcel C25 = "0.21"
file tab1.xls saved

. putexcel C26 = "(0.29)"
file tab1.xls saved

. putexcel C27 = "0.26"
file tab1.xls saved

. putexcel C28 = "(0.26)"
file tab1.xls saved

. 
. putexcel D6 = "0.17"
file tab1.xls saved

. putexcel D7 = "(0.39)"
file tab1.xls saved

. putexcel D8 = "7.59"
file tab1.xls saved

. putexcel D9 = "(4.19)"
file tab1.xls saved

. putexcel D10 = "0.20"
file tab1.xls saved

. putexcel D11 = "(0.41)"
file tab1.xls saved

. putexcel D12 = "0.20"
file tab1.xls saved

. putexcel D13 = "(0.41)"
file tab1.xls saved

. putexcel D14 = "0.31"
file tab1.xls saved

. putexcel D15 = "(0.46)"
file tab1.xls saved

. putexcel D16 = "0.00"
file tab1.xls saved

. putexcel D17 = "(0.00)"
file tab1.xls saved

. putexcel D21 = "0.63"
file tab1.xls saved

. putexcel D22 = "(0.39)"
file tab1.xls saved

. putexcel D23 = "0.59"
file tab1.xls saved

. putexcel D24 = "(0.34)"
file tab1.xls saved

. putexcel D25 = "0.16"
file tab1.xls saved

. putexcel D26 = "(0.26)"
file tab1.xls saved

. putexcel D27 = "0.29"
file tab1.xls saved

. putexcel D28 = "(0.28)"
file tab1.xls saved

. 
. putexcel E6 = "0.686"
file tab1.xls saved

. putexcel E8 = "0.221"
file tab1.xls saved

. putexcel E10 = "0.493"
file tab1.xls saved

. putexcel E12 = "0.538"
file tab1.xls saved

. putexcel E14 = "0.920"
file tab1.xls saved

. putexcel E16 = "0.000"
file tab1.xls saved

. putexcel E21 = "0.005"
file tab1.xls saved

. putexcel E23 = "0.099"
file tab1.xls saved

. putexcel E25 = "0.328"
file tab1.xls saved

. putexcel E27 = "0.539"
file tab1.xls saved

. 
. 
. **************************************************
. *Table 2: Electoral Pressures and Pork Utilization
. **************************************************
. 
. reg cdf_util reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(1, 40)          =       8.86
                                                Prob > F          =     0.0049
                                                R-squared         =     0.0386
                                                Root MSE          =     .35814

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     cdf_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1477992   .0496418     2.98   0.005     .0474694     .248129
        _cons |   .4818703   .0413083    11.67   0.000     .3983831    .5653575
-------------------------------------------------------------------------------

. estimates store reg1

. reg cdf_util reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(6, 40)          =       4.32
                                                Prob > F          =     0.0019
                                                R-squared         =     0.1166
                                                Root MSE          =     .34886

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     cdf_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1487309   .0537741     2.77   0.009     .0400494    .2574123
       female |   .0487409   .0596343     0.82   0.419    -.0717844    .1692663
      officer |   .1484803   .0803683     1.85   0.072    -.0139502    .3109107
   experience |   .0122245    .006436     1.90   0.065     -.000783    .0252321
    celebrity |   .0992268   .0516333     1.92   0.062    -.0051281    .2035816
   term_ender |  -.0570031   .1162873    -0.49   0.627    -.2920285    .1780222
        _cons |   .3294728   .0674475     4.88   0.000     .1931564    .4657892
-------------------------------------------------------------------------------

. estimates store reg2

. areg cdf_util reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        160
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       6.50
                                                Prob > F          =     0.0001
                                                R-squared         =     0.4003
                                                Adj R-squared     =     0.3469
                                                Root MSE          =     0.2943

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     cdf_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1238633    .049192     2.52   0.016     .0244425    .2232841
       female |   .0397769   .0732539     0.54   0.590    -.1082748    .1878286
      officer |   .1161082    .064516     1.80   0.079    -.0142835    .2464999
   experience |   .0183204   .0054455     3.36   0.002     .0073146    .0293261
    celebrity |     .10931   .0582129     1.88   0.068    -.0083426    .2269627
   term_ender |  -.0891033   .1139304    -0.78   0.439    -.3193652    .1411585
        _cons |   .2955379   .0634328     4.66   0.000     .1673355    .4237403
-------------------------------------------------------------------------------

. estimates store reg3

. reg pdaf_util reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(1, 40)          =       4.19
                                                Prob > F          =     0.0474
                                                R-squared         =     0.0213
                                                Root MSE          =     .39405

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
    pdaf_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1195264   .0584257     2.05   0.047     .0014437    .2376091
        _cons |    .587538    .049011    11.99   0.000      .488483     .686593
-------------------------------------------------------------------------------

. estimates store reg4

. reg pdaf_util reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(6, 40)          =       5.77
                                                Prob > F          =     0.0002
                                                R-squared         =     0.1575
                                                Root MSE          =     .37156

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
    pdaf_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1193888   .0611552     1.95   0.058    -.0042106    .2429881
       female |    .082233   .0800231     1.03   0.310    -.0794996    .2439656
      officer |   .1518517   .0857446     1.77   0.084    -.0214445    .3251479
   experience |   .0226237    .006421     3.52   0.001     .0096464     .035601
    celebrity |   .0969091   .0659677     1.47   0.150    -.0364165    .2302348
   term_ender |  -.1290616   .1387288    -0.93   0.358    -.4094431    .1513199
        _cons |   .3513558   .0675392     5.20   0.000      .214854    .4878575
-------------------------------------------------------------------------------

. estimates store reg5

. areg pdaf_util reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        159
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       5.75
                                                Prob > F          =     0.0002
                                                R-squared         =     0.2286
                                                Adj R-squared     =     0.1595
                                                Root MSE          =     0.3640

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
    pdaf_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1300619   .0650394     2.00   0.052    -.0013877    .2615115
       female |   .0960194   .0862431     1.11   0.272    -.0782844    .2703232
      officer |   .1495901   .0830584     1.80   0.079    -.0182771    .3174573
   experience |   .0224541    .006089     3.69   0.001     .0101477    .0347605
    celebrity |   .0806956   .0717735     1.12   0.268     -.064364    .2257553
   term_ender |  -.1561971   .1483598    -1.05   0.299    -.4560434    .1436492
        _cons |   .3538885   .0676341     5.23   0.000     .2171949     .490582
-------------------------------------------------------------------------------

. estimates store reg6

. reg dpwhca_util reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =         80
                                                F(1, 34)          =       1.74
                                                Prob > F          =     0.1964
                                                R-squared         =     0.0128
                                                Root MSE          =     .32496

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
  dpwhca_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |    .073562   .0558204     1.32   0.196    -.0398786    .1870027
        _cons |   .8574111   .0404626    21.19   0.000     .7751812     .939641
-------------------------------------------------------------------------------

. estimates store reg7

. reg dpwhca_util reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =         80
                                                F(6, 34)          =       0.65
                                                Prob > F          =     0.6903
                                                R-squared         =     0.0410
                                                Root MSE          =     .33106

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
  dpwhca_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0835889   .0586488     1.43   0.163    -.0355998    .2027775
       female |  -.0268395   .0791706    -0.34   0.737    -.1877334    .1340545
      officer |   .0273989   .0606897     0.45   0.655    -.0959374    .1507353
   experience |   .0098478   .0080432     1.22   0.229    -.0064979    .0261935
    celebrity |  -.0042757   .0673037    -0.06   0.950    -.1410533     .132502
   term_ender |  -.0024556   .1614022    -0.02   0.988    -.3304643    .3255532
        _cons |   .7720402   .1000541     7.72   0.000     .5687058    .9753746
-------------------------------------------------------------------------------

. estimates store reg8

. areg dpwhca_util reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =         80
Absorbed variable: year                         No. of categories =          6
                                                F(   6,     34)   =       1.28
                                                Prob > F          =     0.2937
                                                R-squared         =     0.4459
                                                Adj R-squared     =     0.3563
                                                Root MSE          =     0.2607

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
  dpwhca_util |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0451685   .0511103     0.88   0.383    -.0587002    .1490371
       female |   .0509779   .0449239     1.13   0.264    -.0403185    .1422743
      officer |  -.0006446   .0666187    -0.01   0.992    -.1360302     .134741
   experience |   .0063937   .0065548     0.98   0.336    -.0069272    .0197146
    celebrity |  -.0223205   .0520162    -0.43   0.671    -.1280301    .0833892
   term_ender |    .041495   .1104222     0.38   0.709    -.1829098    .2658999
        _cons |   .8113655   .0779982    10.40   0.000      .652854     .969877
-------------------------------------------------------------------------------

. estimates store reg9

. 
. outreg2 [reg1 reg2 reg3 reg4 reg5 reg6 reg7 reg8 reg9] using  "tab2.xls",replace auto(2) 
tab2.xls
dir : seeout

. 
. 
. **********************************************************************
. *Table 3: Electoral Pressures and Ratio of Targeted Pork to Total Pork
. **********************************************************************
. 
. reg cdf_mix reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(1, 40)          =       2.84
                                                Prob > F          =     0.0995
                                                R-squared         =     0.0152
                                                Root MSE          =     .35215

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
      cdf_mix |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   -.090214   .0534937    -1.69   0.099    -.1983288    .0179008
        _cons |   .6838208   .0498579    13.72   0.000     .5830542    .7845874
-------------------------------------------------------------------------------

. estimates store reg1

. reg cdf_mix reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(6, 40)          =       2.20
                                                Prob > F          =     0.0635
                                                R-squared         =     0.0844
                                                Root MSE          =     .34506

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
      cdf_mix |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0803621   .0537293    -1.50   0.143    -.1889531     .028229
       female |    .045326   .0789524     0.57   0.569    -.1142427    .2048948
      officer |   .0992351   .0595153     1.67   0.103    -.0210499    .2195201
   experience |   .0068834   .0060433     1.14   0.261    -.0053306    .0190975
    celebrity |   .1694989    .069029     2.46   0.019     .0299861    .3090118
   term_ender |  -.0063025   .1448761    -0.04   0.966    -.2991079     .286503
        _cons |   .5593613   .0881123     6.35   0.000     .3812796    .7374429
-------------------------------------------------------------------------------

. estimates store reg2

. areg cdf_mix reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        160
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       2.08
                                                Prob > F          =     0.0777
                                                R-squared         =     0.1452
                                                Adj R-squared     =     0.0691
                                                Root MSE          =     0.3413

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
      cdf_mix |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   -.067397   .0563538    -1.20   0.239    -.1812922    .0464982
       female |   .0604109   .0830386     0.73   0.471    -.1074164    .2282383
      officer |   .0913532   .0577449     1.58   0.122    -.0253537    .2080601
   experience |   .0079294   .0061244     1.29   0.203    -.0044485    .0203073
    celebrity |   .1631206   .0702418     2.32   0.025     .0211565    .3050847
   term_ender |  -.0400151   .1496554    -0.27   0.791      -.34248    .2624498
        _cons |   .5501822   .0842373     6.53   0.000     .3799323     .720432
-------------------------------------------------------------------------------

. estimates store reg3

. reg pdaf_mix reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(1, 40)          =       0.40
                                                Prob > F          =     0.5318
                                                R-squared         =     0.0023
                                                Root MSE          =     .35833

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     pdaf_mix |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0352332   .0558634    -0.63   0.532    -.1481374     .077671
        _cons |    .500401   .0425473    11.76   0.000     .4144098    .5863922
-------------------------------------------------------------------------------

. estimates store reg4

. reg pdaf_mix reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(6, 40)          =       1.21
                                                Prob > F          =     0.3225
                                                R-squared         =     0.0278
                                                Root MSE          =     .35949

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     pdaf_mix |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0275118   .0571848    -0.48   0.633    -.1430866     .088063
       female |    .048527   .0526106     0.92   0.362    -.0578029     .154857
      officer |   .0637825   .0789135     0.81   0.424    -.0957077    .2232726
   experience |   -.002563    .006279    -0.41   0.685    -.0152534    .0101274
    celebrity |   .1007782   .0735188     1.37   0.178    -.0478088    .2493652
   term_ender |   .0582029   .1285517     0.45   0.653    -.2016098    .3180156
        _cons |   .4704459   .0806208     5.84   0.000     .3075053    .6333866
-------------------------------------------------------------------------------

. estimates store reg5

. areg pdaf_mix reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        159
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       1.16
                                                Prob > F          =     0.3468
                                                R-squared         =     0.1107
                                                Adj R-squared     =     0.0309
                                                Root MSE          =     0.3520

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     pdaf_mix |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   -.043202   .0627909    -0.69   0.495     -.170107    .0837031
       female |   .0548422   .0566288     0.97   0.339    -.0596089    .1692934
      officer |   .0553439   .0651699     0.85   0.401    -.0763694    .1870571
   experience |   .0019637   .0059791     0.33   0.744    -.0101205    .0140479
    celebrity |   .1034853   .0703496     1.47   0.149    -.0386964    .2456671
   term_ender |   .0392273   .1295803     0.30   0.764    -.2226642    .3011188
        _cons |    .440379   .0852003     5.17   0.000     .2681828    .6125753
-------------------------------------------------------------------------------

. estimates store reg6

. 
. outreg2 [reg1 reg2 reg3 reg4 reg5 reg6] using  "tab3.xls",replace auto(2) 
tab3.xls
dir : seeout

. 
. 
. ***************************************************************************************
. *Table 4: Electoral Pressures and Ratio of Pork to Home Province to Total Targeted Pork
. ***************************************************************************************
. 
. reg cdf_homeprov reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(1, 40)          =       0.98
                                                Prob > F          =     0.3280
                                                R-squared         =     0.0059
                                                Root MSE          =      .2762

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
 cdf_homeprov |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0439251   .0443614    -0.99   0.328    -.1335828    .0457325
        _cons |    .208698    .043512     4.80   0.000      .120757     .296639
-------------------------------------------------------------------------------

. estimates store reg1

. reg cdf_homeprov reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(6, 40)          =       1.11
                                                Prob > F          =     0.3756
                                                R-squared         =     0.0528
                                                Root MSE          =     .27398

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
 cdf_homeprov |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0544672   .0466004    -1.17   0.249    -.1486501    .0397156
       female |  -.1139651   .0888362    -1.28   0.207    -.2935097    .0655795
      officer |  -.1115318   .0648437    -1.72   0.093    -.2425858    .0195221
   experience |  -.0013381   .0066464    -0.20   0.841    -.0147709    .0120947
    celebrity |   .0092772   .0908858     0.10   0.919    -.1744099    .1929642
   term_ender |  -.1066055   .0777482    -1.37   0.178    -.2637405    .0505296
        _cons |   .2695142   .0864299     3.12   0.003     .0948328    .4441956
-------------------------------------------------------------------------------

. estimates store reg2

. areg cdf_homeprov reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        160
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       1.05
                                                Prob > F          =     0.4083
                                                R-squared         =     0.1054
                                                Adj R-squared     =     0.0257
                                                Root MSE          =     0.2726

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
 cdf_homeprov |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0582382   .0441478    -1.32   0.195    -.1474642    .0309877
       female |  -.0949197   .0863897    -1.10   0.278    -.2695198    .0796803
      officer |  -.1007295   .0610225    -1.65   0.107    -.2240606    .0226016
   experience |   .0006098   .0066735     0.09   0.928    -.0128778    .0140975
    celebrity |  -.0110555     .08568    -0.13   0.898    -.1842212    .1621102
   term_ender |  -.1004544   .0787179    -1.28   0.209    -.2595492    .0586404
        _cons |    .254024   .0811303     3.13   0.003     .0900536    .4179944
-------------------------------------------------------------------------------

. estimates store reg3

. reg pdaf_homeprov reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(1, 40)          =       0.00
                                                Prob > F          =     0.9868
                                                R-squared         =     0.0000
                                                Root MSE          =     .32433

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
pdaf_homeprov |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0010277   .0618282    -0.02   0.987    -.1259871    .1239317
        _cons |    .220465   .0441335     5.00   0.000     .1312678    .3096622
-------------------------------------------------------------------------------

. estimates store reg4

. reg pdaf_homeprov reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(6, 40)          =       1.59
                                                Prob > F          =     0.1751
                                                R-squared         =     0.0635
                                                Root MSE          =     .31897

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
pdaf_homeprov |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0016128   .0667641     0.02   0.981    -.1333225     .136548
       female |  -.0519661    .093207    -0.56   0.580    -.2403444    .1364122
      officer |   -.160173   .0584285    -2.74   0.009    -.2782615   -.0420845
   experience |  -.0033443    .006221    -0.54   0.594    -.0159175    .0092289
    celebrity |   .1192293   .0816464     1.46   0.152    -.0457843    .2842428
   term_ender |  -.0601434   .0884811    -0.68   0.501    -.2389703    .1186835
        _cons |   .2603536   .0934324     2.79   0.008     .0715196    .4491876
-------------------------------------------------------------------------------

. estimates store reg5

. areg pdaf_homeprov reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        159
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       2.07
                                                Prob > F          =     0.0781
                                                R-squared         =     0.1182
                                                Adj R-squared     =     0.0391
                                                Root MSE          =     0.3169

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
pdaf_homeprov |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0119179   .0658502    -0.18   0.857    -.1450061    .1211702
       female |  -.0381629   .0890435    -0.43   0.671    -.2181265    .1418007
      officer |  -.1519772   .0490698    -3.10   0.004    -.2511509   -.0528034
   experience |   .0003022   .0057847     0.05   0.959     -.011389    .0119934
    celebrity |   .1097227   .0809194     1.36   0.183    -.0538215    .2732668
   term_ender |  -.0390425   .0962671    -0.41   0.687    -.2336056    .1555206
        _cons |   .2315049   .0892897     2.59   0.013     .0510437    .4119661
-------------------------------------------------------------------------------

. estimates store reg6

. reg dpwhca_homeprov reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =         80
                                                F(1, 34)          =       3.82
                                                Prob > F          =     0.0590
                                                R-squared         =     0.0250
                                                Root MSE          =     .28979

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
dpwhca_home~v |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0923368   .0472531    -1.95   0.059    -.1883667    .0036931
        _cons |   .2456137    .059286     4.14   0.000     .1251301    .3660972
-------------------------------------------------------------------------------

. estimates store reg7

. reg dpwhca_homeprov reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =         80
                                                F(6, 34)          =       1.96
                                                Prob > F          =     0.0987
                                                R-squared         =     0.1555
                                                Root MSE          =     .27877

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
dpwhca_home~v |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.1123967   .0467985    -2.40   0.022    -.2075026   -.0172908
       female |   -.143395   .0900622    -1.59   0.121    -.3264233    .0396334
      officer |  -.0843545   .0793536    -1.06   0.295    -.2456204    .0769114
   experience |  -.0160846   .0103066    -1.56   0.128    -.0370302     .004861
    celebrity |  -.0983043   .1170714    -0.84   0.407     -.336222    .1396135
   term_ender |    -.01914   .1239213    -0.15   0.878    -.2709784    .2326983
        _cons |   .4580894   .1419118     3.23   0.003     .1696899    .7464889
-------------------------------------------------------------------------------

. estimates store reg8

. areg dpwhca_homeprov reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num
> )

Linear regression, absorbing indicators         Number of obs     =         80
Absorbed variable: year                         No. of categories =          6
                                                F(   6,     34)   =       2.39
                                                Prob > F          =     0.0492
                                                R-squared         =     0.1839
                                                Adj R-squared     =     0.0519
                                                Root MSE          =     0.2839

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
dpwhca_home~v |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.1181645   .0472606    -2.50   0.017    -.2142096   -.0221194
       female |  -.1476394   .0959128    -1.54   0.133    -.3425576    .0472788
      officer |  -.0871111   .0815456    -1.07   0.293    -.2528317    .0786096
   experience |  -.0181255   .0100875    -1.80   0.081    -.0386256    .0023747
    celebrity |  -.1100423   .1187106    -0.93   0.360    -.3512912    .1312066
   term_ender |   .0184059    .116524     0.16   0.875    -.2183993     .255211
        _cons |   .4782942   .1401322     3.41   0.002     .1935114     .763077
-------------------------------------------------------------------------------

. estimates store reg9

. 
. outreg2 [reg1 reg2 reg3 reg4 reg5 reg6 reg7 reg8 reg9] using  "tab4.xls",replace auto(2) 
tab4.xls
dir : seeout

. 
. 
. ******************************************************************************
. *Table 5: Electoral Pressures and Herfindahl--Hirschman Index of Targeted Pork
. ******************************************************************************
. 
. *Total CDF: What explains concentration of pork across provinces?
. reg cdf_hhi reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(1, 40)          =       0.38
                                                Prob > F          =     0.5393
                                                R-squared         =     0.0028
                                                Root MSE          =     .26657

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
      cdf_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0291173   .0470221     0.62   0.539     -.065918    .1241525
        _cons |   .2641624   .0299132     8.83   0.000     .2037055    .3246193
-------------------------------------------------------------------------------

. estimates store reg1

. reg cdf_hhi reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        160
                                                F(6, 40)          =       2.16
                                                Prob > F          =     0.0677
                                                R-squared         =     0.0464
                                                Root MSE          =     .26491

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
      cdf_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0240826   .0471083     0.51   0.612    -.0711268     .119292
       female |  -.0549444   .0642992    -0.85   0.398    -.1848979    .0750091
      officer |  -.1201532   .0447164    -2.69   0.010    -.2105283    -.029778
   experience |   .0056796   .0043328     1.31   0.197    -.0030772    .0144365
    celebrity |   .0581338   .0502086     1.16   0.254    -.0433416    .1596092
   term_ender |  -.1324917   .0706112    -1.88   0.068    -.2752023    .0102188
        _cons |   .2479971   .0685969     3.62   0.001     .1093576    .3866367
-------------------------------------------------------------------------------

. estimates store reg2

. areg cdf_hhi reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        160
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       1.92
                                                Prob > F          =     0.1012
                                                R-squared         =     0.2416
                                                Adj R-squared     =     0.1740
                                                Root MSE          =     0.2418

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
      cdf_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0203572   .0448569     0.45   0.652     -.070302    .1110164
       female |  -.0241841   .0598494    -0.40   0.688    -.1451442    .0967761
      officer |  -.1044556   .0399911    -2.61   0.013    -.1852806   -.0236305
   experience |   .0090811   .0039946     2.27   0.028     .0010077    .0171545
    celebrity |   .0309626   .0483089     0.64   0.525    -.0666732    .1285985
   term_ender |  -.1129386   .0760517    -1.49   0.145    -.2666448    .0407675
        _cons |   .2178311   .0629453     3.46   0.001     .0906139    .3450483
-------------------------------------------------------------------------------

. estimates store reg3

. reg pdaf_hhi reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(1, 40)          =       0.56
                                                Prob > F          =     0.4576
                                                R-squared         =     0.0038
                                                Root MSE          =     .31172

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     pdaf_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0396737   .0528915    -0.75   0.458    -.1465715    .0672241
        _cons |    .301872   .0357217     8.45   0.000     .2296757    .3740683
-------------------------------------------------------------------------------

. estimates store reg4

. reg pdaf_hhi reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =        159
                                                F(6, 40)          =       3.01
                                                Prob > F          =     0.0159
                                                R-squared         =     0.0701
                                                Root MSE          =     .30609

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     pdaf_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0391779   .0523444    -0.75   0.459    -.1449699    .0666141
       female |  -.0004288   .0597577    -0.01   0.994    -.1212036     .120346
      officer |  -.1680438   .0527581    -3.19   0.003     -.274672   -.0614157
   experience |   .0017749   .0057427     0.31   0.759    -.0098314    .0133813
    celebrity |   .1200437    .054597     2.20   0.034     .0096991    .2303884
   term_ender |   -.102299   .0914787    -1.12   0.270    -.2871843    .0825863
        _cons |   .2977343   .0782011     3.81   0.000     .1396839    .4557847
-------------------------------------------------------------------------------

. estimates store reg5

. areg pdaf_hhi reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =        159
Absorbed variable: year                         No. of categories =          8
                                                F(   6,     40)   =       2.49
                                                Prob > F          =     0.0387
                                                R-squared         =     0.1912
                                                Adj R-squared     =     0.1187
                                                Root MSE          =     0.2923

                                (Std. Err. adjusted for 41 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
     pdaf_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |  -.0478215   .0498667    -0.96   0.343    -.1486059     .052963
       female |   .0265631   .0546835     0.49   0.630    -.0839565    .1370826
      officer |  -.1506135   .0515814    -2.92   0.006    -.2548635   -.0463636
   experience |     .00523   .0054085     0.97   0.339     -.005701     .016161
    celebrity |    .095341   .0550125     1.73   0.091    -.0158435    .2065254
   term_ender |  -.0781858   .0980824    -0.80   0.430    -.2764178    .1200462
        _cons |   .2684189   .0756329     3.55   0.001     .1155591    .4212788
-------------------------------------------------------------------------------

. estimates store reg6

. reg dpwhca_hhi reelectionist, vce(cl sen_num)

Linear regression                               Number of obs     =         80
                                                F(1, 34)          =       2.01
                                                Prob > F          =     0.1657
                                                R-squared         =     0.0275
                                                Root MSE          =     .32731

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
   dpwhca_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .1095238   .0773163     1.42   0.166    -.0476018    .2666494
        _cons |   .3696375   .0460782     8.02   0.000     .2759954    .4632797
-------------------------------------------------------------------------------

. estimates store reg7

. reg dpwhca_hhi reelectionist female officer experience celebrity term_ender, vce(cl sen_num)

Linear regression                               Number of obs     =         80
                                                F(6, 34)          =       0.72
                                                Prob > F          =     0.6347
                                                R-squared         =     0.0520
                                                Root MSE          =     .33404

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
   dpwhca_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |    .097187   .0913782     1.06   0.295    -.0885158    .2828897
       female |  -.0094087   .1147869    -0.08   0.935    -.2426838    .2238663
      officer |  -.0573022   .1002179    -0.57   0.571    -.2609696    .1463651
   experience |  -.0071666   .0069584    -1.03   0.310    -.0213078    .0069747
    celebrity |  -.0790643   .0833021    -0.95   0.349    -.2483546     .090226
   term_ender |  -.0208805   .1070814    -0.19   0.847    -.2384961    .1967351
        _cons |   .4725046   .1144406     4.13   0.000     .2399334    .7050758
-------------------------------------------------------------------------------

. estimates store reg8

. areg dpwhca_hhi reelectionist female officer experience celebrity term_ender, absorb(year) vce(cl sen_num)

Linear regression, absorbing indicators         Number of obs     =         80
Absorbed variable: year                         No. of categories =          6
                                                F(   6,     34)   =       0.43
                                                Prob > F          =     0.8528
                                                R-squared         =     0.2766
                                                Adj R-squared     =     0.1596
                                                Root MSE          =     0.3023

                                (Std. Err. adjusted for 35 clusters in sen_num)
-------------------------------------------------------------------------------
              |               Robust
   dpwhca_hhi |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
reelectionist |   .0827664   .0802277     1.03   0.310     -.080276    .2458087
       female |  -.0312517   .1110133    -0.28   0.780    -.2568578    .1943544
      officer |  -.0430624   .0754403    -0.57   0.572    -.1963756    .1102508
   experience |  -.0030298   .0078689    -0.39   0.703    -.0190214    .0129617
    celebrity |  -.0573723   .0838769    -0.68   0.499    -.2278307    .1130861
   term_ender |  -.0277356   .0913767    -0.30   0.763    -.2134355    .1579642
        _cons |   .4397615   .1226709     3.58   0.001     .1904643    .6890588
-------------------------------------------------------------------------------

. estimates store reg9

. 
. outreg2 [reg1 reg2 reg3 reg4 reg5 reg6 reg7 reg8 reg9] using  "tab5.xls",replace auto(2) 
tab5.xls
dir : seeout

. 
. 
. log close
      name:  <unnamed>
       log:  /Users/nravanilla/Desktop/Senate Pork Replication Files/senate_pork.log
  log type:  text
 closed on:  29 Apr 2022, 14:30:19
----------------------------------------------------------------------------------------------------------------
